9 citations · 31 across the 32 of their papers we have counts for
14 papers · 1 filter
Can Large Language Models Understand You Better? An MBTI Personality Detection Dataset Aligned with Population Traits
Bohan Li, Jiannan Guan, Longxu Dou +12
The Myers-Briggs Type Indicator (MBTI) is one of the most influential personality theories reflecting individual differences in thinking, feeling, and behaving. MBTI personality de…
SCITAT: A Question Answering Benchmark for Scientific Tables and Text Covering Diverse Reasoning Types
Xuanliang Zhang, Dingzirui Wang, Baoxin Wang +6
Scientific question answering (SQA) is an important task aimed at answering questions based on papers. However, current SQA datasets have limited reasoning types and neglect the re…
SailCompass: Towards Reproducible and Robust Evaluation for Southeast Asian Languages
Jia Guo, Longxu Dou, Guangtao Zeng +3
In this paper, we introduce SailCompass, a reproducible and robust evaluation benchmark for assessing Large Language Models (LLMs) on Southeast Asian Languages (SEA). SailCompass e…
A Survey on Large Language Model-Based Social Agents in Game-Theoretic Scenarios
Xiachong Feng, Longxu Dou, Ella Li +5
Game-theoretic scenarios have become pivotal in evaluating the social intelligence of Large Language Model (LLM)-based social agents. While numerous studies have explored these age…
In-Context Transfer Learning: Demonstration Synthesis by Transferring Similar Tasks
Dingzirui Wang, Xuanliang Zhang, Qiguang Chen +9
In-context learning (ICL) is an effective approach to help large language models (LLMs) adapt to various tasks by providing demonstrations of the target task. Considering the high…
FLEXTAF: Enhancing Table Reasoning with Flexible Tabular Formats
Xuanliang Zhang, Dingzirui Wang, Longxu Dou +4
The table reasoning task aims to answer the question according to the given table. Currently, using Large Language Models (LLMs) is the predominant method for table reasoning. Most…
DAC: Decomposed Automation Correction for Text-to-SQL
Dingzirui Wang, Longxu Dou, Xuanliang Zhang +2
Text-to-SQL is an important task that helps people obtain information from databases by automatically generating SQL queries. Considering the brilliant performance, approaches base…
Scaling Laws with Vocabulary: Larger Models Deserve Larger Vocabularies
Chaofan Tao, Qian Liu, Longxu Dou +5
Research on scaling large language models (LLMs) has primarily focused on model parameters and training data size, overlooking the role of vocabulary size. We investigate how vocab…
RegMix: Data Mixture as Regression for Language Model Pre-training
Qian Liu, Xiaosen Zheng, Niklas Muennighoff +5
The data mixture for large language model pre-training significantly impacts performance, yet how to determine an effective mixture remains unclear. We propose RegMix to automatica…
Sailor: Open Language Models for South-East Asia
Longxu Dou, Qian Liu, Guangtao Zeng +4
We present Sailor, a family of open language models ranging from 0.5B to 7B parameters, tailored for South-East Asian (SEA) languages. These models are continually pre-trained from…
Enhancing Numerical Reasoning with the Guidance of Reliable Reasoning Processes
Dingzirui Wang, Longxu Dou, Xuanliang Zhang +2
Numerical reasoning is an essential ability for NLP systems to handle numeric information. Recent research indicates that fine-tuning a small-scale model to learn generating reason…
A Survey of Table Reasoning with Large Language Models
Xuanliang Zhang, Dingzirui Wang, Longxu Dou +2
Table reasoning, which aims to generate the corresponding answer to the question following the user requirement according to the provided table, and optionally a text description o…
MURRE: Multi-Hop Table Retrieval with Removal for Open-Domain Text-to-SQL
Xuanliang Zhang, Dingzirui Wang, Longxu Dou +2
The open-domain text-to-SQL task aims to retrieve question-relevant tables from massive databases and generate SQL. However, the performance of current methods is constrained by si…
Improving Demonstration Diversity by Human-Free Fusing for Text-to-SQL
Dingzirui Wang, Longxu Dou, Xuanliang Zhang +2
Currently, the in-context learning method based on large language models (LLMs) has become the mainstream of text-to-SQL research. Previous works have discussed how to select demon…